Job Description

At EY, you’ll have the chance to build a career as unique as you are, with the global scale, support, inclusive culture and technology to become the best version of you. And we’re counting on your unique voice and perspective to help EY become even better, too. Join us and build an exceptional experience for yourself, and a better working world for all.

Applied Optimisation Scientist (Lead / Senior Level)

Career Family

Applied Optimization & Advanced Analytics

Role Type

Full Time

Experience: 8–12+ years

The Opportunity

We are looking for a highly skilled Applied Optimisation Scientist to design, extend, and validate large-scale mathematical optimisation models supporting strategic mine planning and optimisation platforms. This role focuses on solving complex, high-impact planning problems using advanced optimisation techniques to drive long-term operational and investment decisions. You will work at the intersection of mathematical modelling, software engineering, and domain-specific problem-solving, contributing to mission-critical systems that directly influence business performance. The role requires strong expertise in linear and mixed-integer optimisation, hands-on solver experience, and the ability to translate real-world constraints into scalable optimisation solutions.

Your Key Responsibilities

Optimisation Model Development

• Develop and maintain large-scale LP/MIP optimisation models for mine planning and scheduling.
• Design and implement constraints including capacity, sequencing, blending, cost optimisation, and boundary conditions.
• Support advanced optimisation workflows such as Direct Block Scheduling (DBS).
• Continuously improve model structure and performance for production-grade deployments.

Solver Integration & Performance

• Integrate and configure optimisation solvers such as Gurobi, Maroma, and AMPL.
• Ensure high performance, scalability, and numerical stability of models.
• Diagnose and resolve infeasible solutions, performance bottlenecks, and instability issues.
• Optimize solver parameters and execution strategies for efficiency.

Validation & Quality Assurance

• Validate optimisation outputs through rigorous testing, cross-validation, and alternate formulations.
• Ensure correctness, reliability, and consistency of outputs.
• Take ownership of solution quality and defend results with strong analytical reasoning.

Collaboration & Stakeholder Engagement

• Collaborate with product teams, engineers, and domain experts to translate business problems into mathematical models.
• Communicate optimisation assumptions, trade-offs, and outcomes to both technical and non-technical stakeholders.
• Support decision-making by providing insights derived from optimisation models.

Required Skills

• Strong background in Operations Research, Applied Mathematics, and optimisation techniques.
• Proven experience in Linear Programming (LP) and Mixed Integer Programming (MIP).
• Hands-on experience with Gurobi, Maroma, and AMPL (mandatory).
• Experience with additional solvers such as CPLEX or Xpress is advantageous.
• Strong Python programming skills for model development, integration, and testing.
• Experience handling large-scale, performance-critical datasets.
• Solid understanding of optimisation model performance tuning and stability considerations.
• Preferred Skills & Experience
• Experience in mine planning, supply chain optimisation, or heavy industry use cases.
• Exposure to graph-based optimisation and network flow models.
• Familiarity with enterprise-scale optimisation systems.
• Working knowledge of C# / .NET (preferred).
• Core Technology Stack
• Optimisation Solvers: Gurobi, Maroma, AMPL
• Methods: Linear Programming, Mixed Integer Programming, Network Flow Optimisation, Constraint Modelling
• Programming: Python, AMPL, C#/.NET (preferred)

Key Competencies

• Strong analytical and structured problem-solving skills
• Ability to solve complex real-world optimisation challenges
• Ownership mindset with strong attention to detail
• Effective communication and stakeholder engagement
• Ability to balance model accuracy with computational efficiency

Education

Bachelor’s or master’s degree in operations research, Mathematics, Engineering, Computer Science, or related field.

What We Offer

We offer an opportunity to work on high-impact optimisation problems in a collaborative and innovation-driven environment. You will gain exposure to complex industrial use cases, cutting-edge optimisation techniques, and enterprise-scale systems. We foster continuous learning, encourage technical excellence, and provide opportunities for professional growth and leadership.

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